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Protons and heavier ions have an increased relative biological effectiveness (RBE) compared to photons. While variable RBE models are applied clinically in carbon ion therapy, the RBE in proton therapy is accounted for clinically by applying a constant RBE of 1.1. However, an increasing amount of experimental and clinical data show that also the proton RBE varies spatially within the patient. In addition, the existing carbon ion RBE models give substantially different RBE-weighted dose (often referred to as biological dose) distributions for the same irradiation scenarios. Improving the current RBE calculations is therefore crucial for the treatment received by patients. In this thesis, variables affecting the RBE and biological dose models were studied using the FLUKA Monte Carlo code. In the first part of the thesis, a low-energy proton beam cell irradiation experiment at the Oslo Cyclotron Laboratory (OCL) was implemented in FLUKA (Paper I). Applying the FLUKA implementation, the dose and linear energy transfer (LET) (both the dose-averaged LET (LETd) and LET spectra) were estimated in potential cell irradiation positions. The LETd values increased along the beam path, up to approximately 40 keV/µm in the distal dose-fall off. The LET spectra became narrower with depth in water. Comparisons with a simulated 80 MeV proton beam showed that the OCL beam had significantly higher LETd values and much narrower LET spectra for the same LETd values. The FLUKA implementation of the OCL beam demonstrated the importance of having proper proton beam characteristics to achieve accurate RBE versus LET data. In the second part of the thesis, the RBE model applied clinically in carbon ion therapy in Japan (the microdosimetric kinetic model, MKM) was implemented in FLUKA (Paper II). For the implementation, tables connecting the saturation-corrected dose-mean specific energy (z_1D^*) to particle type and particle kinetic energy were generated. The FLUKA implementation was then used to study the sensitivity of the MKM to variations in the model parameters (Paper III). The created z_1D^* tables agreed well with the tables applied clinically in Japan. The relative changes in the biological dose distributions during the sensitivity study were less than the percentage change of a model parameter. In addition, varying multiple parameters simultaneously had mostly smaller impact on the biological dose than varying parameters separately. The MKM implementation enables conversion from dose distributions obtained with the local effect model (European RBE model) to MKM dose distributions, making direct comparisons to the Japanese clinical carbon ion data possible. In the final part of the thesis, a biological dose model accounting for hypoxia was developed for protons and implemented in FLUKA (Paper IV), as well as in a FLUKA based treatment planning tool (Paper V). The hypoxia model estimates the biological dose as a function of RBE and oxygen enhancement ratio (OER). The OER is a function of the LET and the partial oxygen pressure (pO2), which was estimated in patients using [18F]-EF5 PET images. Areas with low pO2 values were observed in the planning target volume of a head and neck cancer patient, resulting in volumes of lower biological dose than prescribed. Treatment plans optimized with the hypoxia method had a median biological dose corresponded with the prescription dose and physical dose distributions which were increased in the hypoxic areas. The optimization of treatment plans with the hypoxic model showed good potential for including the OER, as well as the RBE, in treatment planning. Overall, this thesis has contributed to knowledge on the RBE and biological dose calculations in proton and carbon ion therapy. Monte Carlo studies of an experimental or clinical proton or carbon ion beam may help reducing the uncertainties in the RBE and biological dose. Given the increase in proton and carbon ion facilities worldwide, improving the accuracy of RBE calculations to give patients the best possible treatment is more relevant than ever. |
